Financial Crime Analytics

FNA Financial Crime Analytics

Follow the money

FNA Platform allows users to see create visual investigation tools to see how companies, banks and people are connected via various links. These dashboards are used for use cases ranging from Know Your Customer (KYC) and Customer's Customer (KYCC) analysis to financial crime investigations and Anti-Money Laundering (AML). FNA can help uncover criminal activity that is hidden from first sight.

FNA Platform also augments existing fraud detection systems by automating the generation of dashboards for case officers and by calculating graph features of the data used in machine learning models.

Key Features

Advanced Graph Analytics with more than 200 algorithms to use as features in fraud models.

Wide range of graph algorithms to identify patterns for AML.

Real-time calculation of new graph properties and queries on mutable graphs.

Scalable operations on graphs with hundreds of millions of nodes and billions of links either installed on-premise or on the cloud.

Easy Integration with APIs that work together with enterprise IT infrastructure, graph databases and external Fraud/AML software.

For Who?

Use Case

Fraud

Automated Detection of Fraud

Method

Payments form networks which can be automatically analyzed by network science algorithms. Existing research on large datasets proved that particular graph properties are good predictors of fraudulent transactions. AML detection is based on detecting suspicious patterns. There is rarely a dataset for true positives that would allow the development of statistical models. However, many of these known patterns can be automatically detected with graph algorithms.